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Record W4411676179 · doi:10.3174/ajnr.a8900

Multiple Synchronous CSF-Venous Fistulas in Spontaneous Intracranial Hypotension: A Multi-Institutional Case Series

2025· article· en· W4411676179 on OpenAlexaff
Ajay A. Madhavan, Timothy J. Amrhein, Michelle L. Kodet, Niklas Lutzen, Michael D. Malinzak, Jeremy K. Cutsforth‐Gregory, Ian T. Mark, Ivan Garza, Eike I. Piechowiak, Lalani Carlton Jones

Bibliographic record

VenueAmerican Journal of Neuroradiology · 2025
Typearticle
Languageen
FieldMedicine
TopicNeurosurgical Procedures and Complications
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsMedicineSeries (stratigraphy)Intracranial HypotensionSpontaneous Intracranial HypotensionAnesthesiaCardiologyInternal medicineCerebrospinal fluid

Abstract

fetched live from OpenAlex

<h3>ABSTRACT</h3> CSF-venous fistulas are a common cause of spontaneous intracranial hypotension. Due to the more routine use of decubitus myelography and advancements in various imaging techniques, recognition of CSF-venous fistulas has increased in recent years. Most commonly, patients harbor only one fistula at the time of myelography (although additional de novo fistulas can arise after treatment). Occasionally, two synchronous CSF-venous fistulas may be seen on a single myelogram. The co-existence of more than two CSF-venous fistulas, however, is quite rare and has only been previously described in two instances. Here, we present a multi-institutional series of sixteen patients with three or more concurrently discovered CSF-venous fistulas, representing the largest cohort of such patients to date. We describe their clinical features, imaging findings, treatment approaches, and outcomes. ABBREVIATIONS: CVF = CSF-venous fistula; CB-CTM = cone beam CT myelogram; DSM = digital subtraction myelography; EID = energy integrating detector; SIH = spontaneous intracranial hypotension; PCD = photon counting detector

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.567

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.270
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2025
Admission routes1
Has abstractyes

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